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--- |
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dataset_info: |
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features: |
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- name: Prospect ID |
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dtype: string |
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- name: Lead Origin |
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dtype: string |
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- name: Lead Source |
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dtype: string |
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- name: Last Activity |
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dtype: string |
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- name: Tags |
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dtype: string |
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- name: What is your current occupation |
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dtype: string |
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- name: Converted |
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dtype: int64 |
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splits: |
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- name: train |
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num_bytes: 79551 |
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num_examples: 568 |
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- name: valid |
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num_bytes: 359736 |
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num_examples: 2559 |
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- name: test |
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num_bytes: 360809 |
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num_examples: 2561 |
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download_size: 241530 |
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dataset_size: 800096 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: valid |
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path: data/valid-* |
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- split: test |
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path: data/test-* |
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--- |
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# Lead Scoring Dataset |
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## Overview |
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This dataset contains lead scoring data for X Education, a company that provides online courses. The dataset is designed for binary classification to predict whether a lead will convert to a customer using an LLM. |
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- **Source**: [Kaggle - Lead Scoring Dataset](https://www.kaggle.com/datasets/amritachatterjee09/lead-scoring-dataset) |
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- **Target Variable**: `Converted` (0 = Not Converted, 1 = Converted) |
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## Features |
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The processed dataset includes the following 7 key features: |
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1. **Prospect ID** - Unique identifier for each lead |
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2. **Lead Origin** - How the lead was generated (API, Landing Page Submission, etc.) |
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3. **Lead Source** - Specific source of the lead (Google, Direct Traffic, Organic Search, etc.) |
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4. **Last Activity** - Most recent interaction (Email Opened, Page Visited, etc.) |
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5. **Tags** - Lead categorization tags (Ringing, Will revert after reading email, etc.) |
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6. **What is your current occupation** - Lead's current job status (Student, Unemployed, etc.) |
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7. **Converted** - Target variable indicating conversion (0/1) |
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## Usage |
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The processed dataset is available on Hugging Face Hub at: `shawhin/lead-scoring-x` |
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```python |
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from datasets import load_dataset |
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# Load the dataset |
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dataset = load_dataset("shawhin/lead-scoring-x") |
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# Access train, validation, and test splits |
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train_data = dataset['train'] |
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valid_data = dataset['valid'] |
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test_data = dataset['test'] |
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``` |
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## License |
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Please refer to the [original Kaggle dataset](https://www.kaggle.com/datasets/amritachatterjee09/lead-scoring-dataset) license for usage terms. |
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